Anesthesia Trials Lack Precise Definitions for Perioperative Disruptions

Standardizing Clinical Clarity in Perioperative Research

The rapid evolution of perioperative medicine has led to a surge in randomized controlled trials evaluating everything from sedative agents to advanced regional anesthesia techniques [1, 2]. While these studies aim to refine clinical practice, the complexity of the surgical environment often introduces unpredictable variables, such as intraoperative hypotension or postoperative delirium, that can confound primary outcomes [3, 4]. Current reporting standards, such as the PRISMA 2020 statement, have improved transparency in evidence synthesis, yet they do not fully address how individual trials manage unexpected deviations from protocol [5, 6]. Without a rigorous method for handling these intercurrent events (occurrences that happen after treatment starts and affect the interpretation of the outcome), clinicians may struggle to determine if a treatment's reported effect is truly representative of real-world practice. A new analysis now examines the use of a specialized statistical framework designed to bring much-needed precision to the interpretation of anesthesia trial results.

Quantifying the Reporting Gap in Major Anesthesia Journals

The researchers conducted a scoping review of randomized controlled trials involving patients receiving anesthesia before surgery to evaluate the clarity of clinical trial objectives. To ensure the analysis reflected high-quality evidence, the study included 139 trials with 100 or more participants published between January 2020 and June 2024. These trials were selected from ten high-impact journals, representing the most influential literature in perioperative medicine. The primary objective of the review was to determine whether these studies reported estimands (precise definitions of the treatment effect being measured that specify how to handle patient-level complications). For the practicing clinician, an estimand provides the necessary context to understand exactly what a trial is attempting to estimate, accounting for real-world complexities like patient non-compliance or the use of rescue medications. The findings indicate a widespread absence of standardized reporting frameworks in anesthesia research; most notably, none of the 139 included trials explicitly used the estimand framework to define their research questions. This omission is significant because without a formal estimand, it is difficult for physicians to discern how the study handled events that occur after randomization, such as a patient switching to a different anesthetic agent due to an adverse reaction or a change in surgical plan. Beyond the lack of a formal framework, the researchers identified several critical attributes that were frequently non-inferable, meaning the information could not be determined from the published text. The target population was not inferable in 44 trials (32%), which limits a clinician's ability to know if the results apply to their specific patient demographic. Furthermore, the treatment condition was not inferable in 21 trials (15%), and the summary measure (the statistical value used to compare the intervention and control groups) was not inferable in 22 trials (16%). These gaps in reporting suggest that even in top-tier journals, the lack of precise definitions may obscure the clinical utility of anesthesia research.

Identifying Common Intercurrent Events and Protocol Deviations

The researchers focused on identifying intercurrent events, which are occurrences that take place after the initiation of treatment and subsequently affect either the interpretation or the very existence of the clinical outcome. For a physician evaluating a trial on a new anesthetic or analgesic, these events represent the real-world friction that can obscure whether an intervention actually achieved its intended effect. Despite their importance in clinical decision-making, an estimand could be inferred in only 27 trials (19%), meaning the vast majority of studies did not clearly define the exact treatment effect they were measuring in relation to these disruptions. Most critically, the researchers found that intercurrent event handling was not inferable in 84 trials (60%), leaving clinicians without a clear understanding of how the study authors statistically accounted for patients who did not follow the protocol. The review categorized the most frequent disruptions that occurred across the 139 included studies, highlighting how often clinical reality diverges from trial design. The most common intercurrent event was not receiving the randomized intervention, which occurred in 64 trials (46%). This frequently happens when a patient is randomized but the intervention is never administered due to logistical errors or sudden clinical changes. Furthermore, treatment discontinuation occurred as an intercurrent event in 38 trials (27%), while treatment switching, where a patient is moved from the study drug to an alternative therapy, occurred in 27 trials (19%). Without a pre-specified plan for these events, the resulting data can be biased, as the final analysis may include or exclude these patients in ways that do not reflect standard clinical practice. Specific challenges inherent to the perioperative environment were also prevalent in the data. The researchers noted that surgery cancellation was an anesthesia-related intercurrent event in 37 trials (27%), a common clinical reality that can terminate a patient's participation before a primary outcome is even measured. Additionally, non-protocolized anesthesia management was an intercurrent event in 17 trials (12%), occurring when a clinician must deviate from the study's strict instructions to ensure patient safety or respond to intraoperative hemodynamic changes. Because 60% of the trials failed to report how they handled such events, physicians are often left to determine for themselves whether the reported benefits of an intervention would hold up in a busy operating room where protocol deviations are frequent.

A New Framework for Interpreting Perioperative Outcomes

To address the lack of clarity in how perioperative disruptions are reported, the researchers developed a structured framework by mapping intercurrent events to intervention-outcome combinations across all 139 included trials. This framework provides a systematic way for clinicians to understand how events like rescue medication or surgical complications interact with the primary goals of a study. By categorizing these events, the authors aim to standardize the estimand framework, which is a precise description of the treatment effect that reflects the clinical question being asked. For a practicing anesthesiologist, this means trial results can be more accurately translated to the bedside, as the framework clarifies whether a drug's reported benefit accounts for the real-world necessity of switching treatments or administering emergency interventions. These findings directly informed the development of a structured, interactive web-based tool linking intercurrent events to intervention-outcome combinations. This digital resource allows researchers and clinicians to visualize how different perioperative events should be handled statistically to maintain the integrity of the trial's conclusions. To ensure the utility and clinical accuracy of the resource, the web-based tool was refined by expert review, incorporating feedback from specialists to align statistical rigor with practical operating room scenarios. The authors conclude that greater collaboration between statisticians and clinicians is essential to ensure that future anesthesia research uses the estimand framework consistently, providing the transparency needed to guide evidence-based practice in complex surgical environments.

References

1. Suga M, Yasuhara J, Watanabe A, et al. Postoperative delirium under general anaesthesia by remimazolam versus propofol: A systematic review and meta-analysis of randomised controlled trials.. Journal of clinical anesthesia. 2025. doi:10.1016/j.jclinane.2024.111735

2. Carvalho CCD, El-Boghdadly K, Guedes IHL, et al. Opioid-free vs. opioid-inclusive anaesthesia with or without regional anaesthesia for postoperative pain: a systematic review with network meta-analysis of randomised controlled trials.. Anaesthesia. 2026. doi:10.1111/anae.70121

3. Kunutsor SK, Hamal PB, Tomassini S, Yeung J, Whitehouse MR, Matharu GS. Clinical effectiveness and safety of spinal anaesthesia compared with general anaesthesia in patients undergoing hip fracture surgery using a consensus-based core outcome set and patient-and public-informed outcomes: a systematic review and meta-analysis of randomised controlled trials.. British journal of anaesthesia. 2022. doi:10.1016/j.bja.2022.07.031

4. Daccache N, Wu Y, Jeffries SD, et al. Safety and recovery profile of patients after inhalational anaesthesia versus target-controlled or manual total intravenous anaesthesia: a systematic review and meta-analysis of randomised controlled trials.. British journal of anaesthesia. 2025. doi:10.1016/j.bja.2025.02.007

5. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Systematic Reviews. 2021. doi:10.1186/s13643-021-01626-4

6. Doleman B, Jakobsen JC, Mathiesen O, Cooper N, Sutton A, Hardman J. Methodologies for network meta-analysis of randomised controlled trials in pain, anaesthesia, and perioperative medicine: a narrative review.. British journal of anaesthesia. 2025. doi:10.1016/j.bja.2024.12.039